An actor-critic framework built on a time-inhomogeneous little q-function and conditional normalizing flows serves as a mesh-free solver for entropy-regularized jump-diffusion control problems and stochastic games.
Policy gradient methods for reinforcement learning with function approximation.Advances in Neural Information Processing Systems, 12
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An Actor-Critic Framework for Continuous-Time Jump-Diffusion Controls with Normalizing Flows
An actor-critic framework built on a time-inhomogeneous little q-function and conditional normalizing flows serves as a mesh-free solver for entropy-regularized jump-diffusion control problems and stochastic games.